Dopplr it seems has been motivated by understanding context and what might be useful in a given situation, where Facebook's embrace of the realtime web has been driven by the faddish pursuit of a competitor.

Regardless, there are useful social models and design patterns that need to be abstracted from the Twitter, Facebook and Dopplr articulations of time, space, serendipity and relevancy, patterns that might enhance other services. There's an assumption that relevance and seredipity can emerge from simply aggregating together news items from social connections. Yet there's a growing anxiety that we're all drinking from a firehose of data.

Why can't Twitter, for example, learn to whom users grant their attention over time...or Facebook understand to whom I'm 'nearby' (at Matt says - 'hereish-and-soonish/thereish-and-thenish'), helping users make relevancy rather than recency based choices, that wire serendipity into the fabric of social software.